Lead Applied Scientist in AGI

2 weeks ago

Bellevue, Washington, United States Amazon Full time

Job ID:
| Services LLC

We are a segment of Amazon's Artificial General Intelligence (AGI) division, dedicated to enhancing customer experiences through contextual and personalized proactive interactions that keep users informed, engaged, and productive without cognitive overload.

Our focus is on developing sophisticated systems that provide engaging, intuitive, and adaptive content recommendations across all Amazon platforms. Our goal is to enable seamless reasoning and customer interactions, exceeding the capabilities of earlier machine learning models.

We seek a dedicated, skilled, and innovative Senior Applied Scientist specializing in Natural Language Processing (NLP), Large Language Models (LLM), Recommender Systems, and/or Information Retrieval, to create and implement scalable solutions for a cutting-edge context-aware personal assistant.

The ideal candidate will possess a robust machine learning background and a passion for pushing the boundaries in one or more of the aforementioned areas.

We value individuals who thrive in dynamic settings, are self-driven to tackle challenging issues, and are committed to delivering significant customer impact through rapid experimentation and iterative improvements based on user feedback.

Key Responsibilities:

As a Senior Applied Scientist, you will utilize your technical knowledge and experience to lead efforts in addressing large, complex challenges, guiding the direction and collaborating with fellow applied scientists and engineers to devise innovative algorithms and modeling techniques that facilitate timely, relevant, and delightful recommendations and interactions.

Your contributions will directly influence our customers through products and services that leverage various machine learning, deep learning, and language model technologies.

You will harness Amazon's diverse data sources and extensive computing capabilities to propel advancements in the state of the art.
BASIC QUALIFICATIONS - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or a related quantitative field, or a Master's degree

  • PhD, or Master's degree with 6+ years of applied research experience
  • 3+ years of experience in developing machine learning models for business applications
  • Proficiency in programming languages such as Java, C++, Python, or similar
PREFERRED QUALIFICATIONS - PhD in Electrical Engineering, Computer Science, or Mathematics with a focus on natural language processing, recommendation systems, information retrieval, or reinforcement learning

  • 4+ years of experience in creating machine learning and deep learning models for large-scale customer-facing products or features
  • Practical experience with LLMs
  • Publications in peer-reviewed NLP/ML conferences (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI)
  • Strong analytical thinking and the ability to innovate, with a history of thought leadership and contributions that have advanced the field
  • Solid software development skills
  • Excellent written and verbal communication abilities
Amazon is committed to fostering a diverse and inclusive workplace.

Amazon is an equal opportunity employer and does not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status.

For individuals with disabilities who would like to request an accommodation, please visit our website for more information.

Amazon's compensation reflects the labor costs across various US geographic markets. The base salary for this position ranges from $150,400/year in our lowest geographic market to $260,000/year in our highest geographic market.

Compensation is determined by several factors, including market location, and may vary based on job-related knowledge, skills, and experience.

Amazon is a total compensation company, and depending on the position offered, equity, sign-on bonuses, and other forms of compensation may be included as part of a comprehensive compensation package, alongside a full range of medical, financial, and/or other benefits. This position will remain open until filled. Candidates are encouraged to apply through our internal or external career site.

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